Station Guardian
Improving crowd management with anonymous crowd monitoring technology
Overview
Increased passenger demand on our infrastructure has led to increased crowd congestion and delays. As passenger numbers increases so does the level of security threat. The 2017 Manchester bombing of Manchester arena is sobering recent example of the dangerous threat posed. Our technology attempts to tackle these issues whilst preserving traveller identities in compliance with GDPR legislation. It is a tool for space owners to improve the experience of space users.
Approach
ACM is based on one of our other technologies developed for the MoD SAPIENT programme. We use a Laser Rangefinder (LIDAR) to track and identify people in real time and understand their behaviour. The technology utilises edge processing with algorithms originally designed in Matlab being converted to C++. Behavioural detection has been developed using deep learning algorithms which can spot unusual behaviour. All data is passed to a centrally held database which is accessed via a web-based GUI.
Solution
Project partner Arup has helped us trial the technology in sites across the U.K in numerous locations including Waterloo station and Manchester arena. We are currently experimenting business cases for both mobile pay-per-use systems and fully installed systems.
Live Crowd Data
See in real time where crowds are and where they are going. Spot issues before they become a serious problem.
Privacy Protected
Our technology takes no personal data from the space users.
Cost Effective
A single unit can cover and area of up to 100m
Automated Alerts
Deep learning can provide automated characterisation of crowd situations and alert operators immediately.
Emergency Response
Automated detection of incidents for rapid emergency response.
